Once when dao is so closely linked to the excessive meaning that it takes over the semantic meaning of the complement, si could be deleted.

dao could appear independently as a final particle (see section 5).


Dong-kyu's utterance in (3a) is one example containing the adverb and the discourse marker.

repercussive questions with -tako ending that indicating a refusal or denial also express the speaker's anger with the help of other linguistic device such as interrogatives, discourse markers.


Sequences of words are required to be written without intervening spaces and some sequences are allowed to be written with or without intervening spaces.

sentence (1a) would have eleven groups in ordinary writings, as their boundaries are indicated with integers in (2).


Much work has been done on the determination of information structure: here we only mention the test using question-answer pairs to identify the "rheme", as the answer to a wh-question.

to the question in (16a) below, we can obtain the answer (16b) in which only nezumi 'mouse' is rhematic, either in the context of a discussion of a small set of animals, e.g.


In contrast, the present theory follows Steedman (2000aSteedman ( , 2000b in assuming that restrictive and nonrestrictive rhemes are semantically and grammatically indistinguishable, and only differ in the nature of the context in which they are uttered.

we draw the following distinctions: the theme is a predication over the existing context or common ground, and the rheme seeks to effect an update on the context or common ground.


Furthermore, maintaining consistency of a constructed corpus is difficult.

we need an annotation tool for improving annotation efficiency and maintaining consistency.


However, in the antecedent clause of (42) the typical quantified expression takes scope by making a non-cyclic, one-fell-swoop movement (May (1985)).

the ellipsis clause is construed as a simple clause because otherwise the antecedent and ellipsis clauses in the multiple sluicing construction will violate the scope parallelism condition.


The labeling criteria provide a mechanism for mapping abstract prosodic labels into a sequence of acoustic correlates of prosody.

prosodically-labeled sentences contain information concerning the correspondence between the phonological and phonetic attributes of the prosodic structure of utterances and their intended meanings.


Speech rhythm is also a psychological correlate of speech timing (an objective instrumental measurement of the duration of segments, syllables, etc.)

in a stressed-time language, stress, pause and relative syllable durations interact to form speech rhythm.


The duration of a foot will differ somewhat depending upon the phonetic structure of the syllables comprising it.

the acoustic realization of a rhythmic foot will be different from the above abstract description.


On the other hand, in NMF, the axis in the reduced space corresponds to a topic, therefore, these axes do not need to be orthogonal.

nMF attempts to find the axis corresponding to the cluster that has documents containing identical words.


We used data sets that had less than 5,000 data elements.


In this paper, we assigned the label to the cluster to assure the accuracy is high, by using dynamic programming.


This is because the local optimum solution obtained by NMF varies according to the initial value.

deciding what initial matrices should be used is a difficult problem, from Wild et al.


Regarding the object function, initial accuracy must be improved.

we took the approach to set the value that had a high accuracy as the initial value.


It is impossible to find the optimal initial value.

the clustering algorithm must take an approach that improves the solution gradually.


Force dynamics in a socio-physical domain derives force dynamics in a cognitive domain.

it is considered that deontic usage derives epistemic usage and the former is more prototypical than the latter.


Instead, it demonstrates various ways of approximating to a subsystem (Giacalone-Ramat 2003: 28).

l2 acquisition, especially the strategy utilized by adult learners, recapitulates the internal factors of the diachronic grammaticalization in the target language more overtly than l1 acquisition.


Some formal (or grammatical) features are specific to hazuda such as the possible occurrence of an inanimate subject, of noun and adjective in the predicate position, the availability of a negative, past, passive or potential form of the embedded predicate.

we can presume that learners are guided by these formal features to become sensitivized to the usage conditions/constraints on epistemic hazuda.


Table 1 shows the experimental result 6 .

our methods, namely multiple classifiers, outperformed single classifiers.


In other words, our method contains the possibility that it can classify a document correctly if a single classifier identifies the class label (p/n) of a document correctly.

the coverage of our method for this dataset is computed as follows: where N is the number of documents in test data.


Furthermore, new NEs are generated everyday, but the content of bilingual dictionaries cannot be updated frequently.

it is necessary to construct a named entity translation (NET) system.


Because of historical links, almost all Koreans have names that are exclusively Hanja (Han-"Chinese, "-ja "characters").

the most straightforward way to translate a Korean name into Chinese is to adopt its Hanja equivalent.


However, in recent years, Koreans have started to transliterate a Chinese person name based on its Mandarin pronunciation.

the name " 馬 英 九 " is transliterated to "마잉주" (Ma Ing-Ju).


In contrast, the Kanji name "小泉純一 郎" (Xiao quan chun yi lang) is used directly in Chinese.

it is very difficult to translate Japanese names written in Korean into Chinese based on phonetic information.


The word meaning is expressed with the primitives, and it can accomplish the computing of correlation in the glossary, finding the thesaurus, and reducing the dimension.

we explore the Chinese text authorship identification with the KNN classifier that adopts the HNC conceptual primitives as the features carrier.


That is, young children believe that they themselves are the center of the universe, and that all the others think in the same way like them.

they fail to adopt points of view other than their own.


To interpret NPs on non-subject position one extends the domain of type <1 > quantifiers: they are treated as reducers of arity of their arguments, that is as functions which when applied to n-ary relations give (n-1)ary relations.

when they apply to binary relations (denotations of transitive VPs) they give sets (considered as unary relations) as result (and sets are denotations of intransitive VPs).


In other words (7) should be interpreted with the object NP (its appropriate extension) taking wide scope over the subject NP.This fact can be represented precisely with the help of the notion of the case extension.

the basic meaning (which should be completed by some existential presuppositions) of (7) is given in (8):(8) (NO TWO LANGUAGES) (SOME AND NOT EVERY STUDENT) nom KNOW What (7) basically means is that there are no (two) languages which are known by some but not by all students and not that for every student there are two languages such that he/she knows them.


Thus the basic meaning (which should be completed by some existential presuppositions) of (7) is given in (8):(8) (NO TWO LANGUAGES) (SOME AND NOT EVERY STUDENT) nom KNOW What (7) basically means is that there are no (two) languages which are known by some but not by all students and not that for every student there are two languages such that he/she knows them.

in this representation the use of the nominative case extension is essential.


In (13) we have a sentence with a non-standard constituent: (13) Leo hates Sue and Bill himself One observes that in the corresponding sentences in Japanese and in Polish preferably co-referential pronouns should be used at the place of himself.

in Polish (14a) is grammatical and the corresponding sentence (14b) with the pronoun sie is not: (14a) Leo nienawidzi Sue a Bill siebie (14b) *Leo nienawidzi Sue a Bill sie The following examples illustrate the constraint on possible conjunctions.


Third, the representation of signed language examples using written gloss-based text has meant that these data have remained essentially inaccessible to other researchers for meaningful peer review.

although introspection and observation can still be of valuable assistance to linguists developing hypotheses regarding signed language use and structure, one must also recognize that intuitions and researcher observations may fail in the absence of clear native signer consensus of phonological or grammatical typicality, markedness or acceptability.


In today's multi-media digital files, the time-aligned annotations appended to segments of the text are read by machine, not the text (i.e., source data) itself, nor, necessarily, a transcription of the source text, whether spoken or signed.

despite what many signed language researchers continue to believe, a full written phonetic or phonological transcription of signed texts is no longer essential in order to conduct corpus-based research at various levels of linguistic analysis, even the phonological.


Importantly, different glosses for the same sign may be used in different contexts to reflect the meaning of that sign in that context.

it is often very difficult to know with certainty which sign form is actually being referred to by a particular gloss because a gloss does not contain any information about sign form.


We maintain this convention in the ELAN annotation files.

the ID-gloss HOUSE appears on an ID-gloss tier as: (3) (As seen in Figure 2, the boxed annotation field delimits a period of time in the digital media during which a sign is articulated and to which the annotation within the field is time-aligned) HOUSE The standard ID-gloss for a sign is found by consulting the Auslan lexical database.


1 Chierchia (2004) and some other authors recently attacked Gricean and neo-Gricean theories of scalar implicature computation, claiming that these theories based on Gricean reasoning cannot account for the scalar implicatures of certain complex sentences involving disjunction etc..

they proposed grammatical (semantic or syntactic) systems for computing scalar implicatures.


If that is the case, there is no room for scalar implicatures to arise of the same propositional content that has been already asserted or entailed.

the following conjunctions/discourses with PA type conjunction/DM are not acceptable: haciman swusek-un mot haysse 'But she didn't ace the exam').


Therefore, the use of only or its equivalent exh operator for generating a scalar implicature is not well justified.

sevi (2005) argues that scalar implicatures are not implicatures and that they are merely entailments of exh (A, Q), where A is taken to be a complete and partial semantic answer to some question Q, which may be explicit or implicit.


While sentences containing even, as well as Japanese scalar mo and Korean scalar to, express some unexpectedness, the lexical items mark that the state or event describe in the hp is not an outlier in terms of the scalar expectations.

the correlational expectation is conserved, although the y-intercept has changed because of the unexpectedness.


Secondly, the community that produces language resources is vitally interested in the tools that are used in that work; in fact, many in the community focus on the development of such tools.

any resource that is a tool that supports the creation of language resources is also defined to be a language resource.


In the case of language resources, we want to sustain their use.

the problem of sustaining language resources can be understood as the problem of maintaining the use of language resources over time.


Where languages are threatened because children are no longer learning them, acquisition planning becomes a priority and the sustained products of language documentation and description are key inputs to the language development activities that are needed.

the sustainability of language depends in part on the sustainability of the language resources that contribute to language development, which will lead to the production of new language resources that can in turn enable further development, and so the cycle of sustainability continues.


verb that precedes the causative suffix.

the algorithm in the check method of the Passive class starts with a yes-no question.


If the desiderative suffix appears after one of the two suffixes, the unprocessed string of the verb phrase begins with the desiderative suffix "ta", followed by one of the four possible strings as listed in Table 1.

the algorithm, after finding out that the head word has been registered, examines four such possible sequences one after another until a match is found.


However for non-constituents, possibly referred to as distituents, the two contexts form independent distributions.

one measure of constituency is identified by the Mutual Information between the pre and post contexts, MI(σ(α, x), σ(α, y)).


In an ergative language like Filipino, subject control and object control cannot be used, for these terms will lead to some problems.

non-subject actor, controller, or syntactic pivot will be used to avoid confusion.


Moreover, although Chang (2008) empirically examined Metcalf's model, no such study was done for Kjellmer's model or for the comparison of the two models.

for a more adequate evaluation, comparison, and improvement of the performance of both of the models, an empirical study with a set of clear criteria for each factor in the two models would seem necessary.


Li and colleagues concluded that, before 6 years of age, most Mandarin-speaking children still have not learned that count classifiers are cues to individuation.

syntactic cues to individuation may emerge much later in Mandarin than in English One problem in comparing classifiers to count syntax is that whereas count syntax specifies only individuation, classifiers also encode item-specific conceptual information, such as the shape, animacy, etc.


As it provides no shape information, it may function mainly to encode individuation.

we might expect children to learn the role of this classifier in individuation earlier.


Studies have generally found that children starting as young as age of 2 1/2 begin to produce classifiers and reach adult understanding at the age of 6 of 7 (e.g., Chien, Lust and Chiang, 2003;Erbaugh, 1986).

using the word extension task, we tested four groups of children between the ages of three and six, and compared their performance to the results obtained from adults in Experiment 2.


Experiment 3 examined the developmental progression of Mandarin-speaing children in their sensitivity to using the general classifier ge as a cue to individuation.

surprisingly, even 6-yearolds did not possess adult's degree of sensitivity to ge, although previous research has found that ge is only used for concrete entities and is the first classifier children acquire (see Chien et al., 2003;Yamamoto, 2005 for reviews), even though Mandarin may encode the mass-count distinction at the level of the classifier, the acquisition progression is by far slower than English children acquiring mass-count syntax.


It entails more specific information about the referents than what mass count syntax provides in English.

it seems likely that although classifiers provide cues to individuation, Mandarin-speaking children may take a longer time to understand individuation than their English peers acquiring mass-count syntax.


However, it is impossible to estimate them.

we have used following weighting methods in our experiments: (1).


The initial results showed that the thresholds were not effective in its purpose such that only an insignificant amount of proxy trigrams were being filtered out.

the Similarity Score Computation process and the use of similarity score thresholds are removed.


This cannot be prevented even for non-fluent trigrams.

part of the reinforced trigram score must still be influenced by the original score.


Also, there is a greater chance of a trigram having proxy trigrams with lower level matches than having proxy trigrams with exact matches.

in order to prevent the scores of the lower level matches to consume the portion of the score that is supposed to be for higher level matches, different score limits are assigned to each match level.


The purpose of doing so is to avoid cases of low frequency collocations such as those which occur once but have high mutual information values because it is the only time they appear together with the target word.

the salience value is a reliable calculator instead of the frequency value.


The studies presented above and most of the related works are based exclusively on the CCG formalism of Steedman and developed in the purpose of a computational realization.

they often ignore the linguistic aspect of language and cannot capture some fine points such as morphological cases in Korean.


Compared to these works based on the CCG formalism, the ACCG formalism that we develop in this paper, is not only a computational but also a linguistic approach, namely it better reflects the linguistic aspect in the Korean natural language processing.

this advantage allows us to parse the Korean language in a more explicit way and to show clearly the morphosyntactic structure of the Korean through our calculations.


Indeed, if Korean-speaking English language learners (ELLs) face exclusively distinctive stress patterns of English, which is not relevant to their L1, they may confront drastic restructuring of their interlanguage stress assignments and deal with unstable prosodic representations across the two languages.

they would be at risk for difficulties in learning to speak and read in English as a stress-sensitive L2 and displaying prosodic information of English words.


Computing emerging difference: For a candidate w in a target subject field i, calculate its emerging difference d ij via comparison with another subject field j as where s i (w) and s j (w) are w's normalized weights in fields i and j (0< i, j ≤n), respectively.

each candidate in each field will have n-1 emerging difference scores corresponding to the n-1 background fields involved in the comparison.


In linguistic terms, rules that determine semantic interpretation are defined on the syntactic rules and structures.

we develop semantic attachment rules for each syntactic rule in our grammar.


By employing the coordinative conjunction axiom, the semantic representation will be augmented with the literals patient(e,x) and patient(e,y), thus making the representation canonical.

the system unifies the query with 'kue' (cake) and 'apel' (apple) for the answer.


Specifically, it asserts object(q,buah), isA(y,q), dan(p,x,q), and patient(e,q).

given the following question: Buah apa yang dimakan Lusi ?


Rather, they are typically built through the trial and error design mechanism that evolution affords.

one or more non-monotonic operators must facilitate this, such as deletion, replacement, and swapping of substructures.


Campbell (1998) and Crowley (1997) added that the semantic aspects of language were overlooked by many of the researchers in historical linguistics.

a study on the semantic change of Cebuano words should be conducted to fill this gap.


Such adverbials, however, are restricted in the case of ga-desideratives as shown in (3).

the contrast on adverbial modification in (3) cannot be explained by their analyses.


Consider (13): (13a) is a passive counterpart of a desiderative in (13b).

another question here is why (11b) cannot be passivized as shown in (12b) while (13b) can as shown in (13a).


It is worth noting that the object of (10a) occurs in the nominative case like other simple stative predicates.

the contrast between (12a) and (12b) is accounted for by our claim that the passivization of the verbalized stative predicate is possible when the non-verbalized plain stative predicate can take a nominative object.


Here we do not go into the detail of the passive morpheme and particle but the point is that there is no accessible object NP which is promoted by passivization once S \ NP nom is derived with ta(i).

the wo-desiderative has no passive counterparts.


Our purpose is to generate a natural sentence that includes subjective phrases.

we use syntactic pieces that have structural information and generate sentences effectively.


Emotional words clearly represent an emotion; for example, a word 'glad' clearly represents a happy emotion.

the lexicons provide useful information for extraction of particular emotion expressing blogs( in section 3.2).


e mean emotions other than e ; when emotion e is sadness, emotions e are joy and fear.

there are two requirements, below, for a blog to be considered as having emotion .


This shows that coherence of emotion affects the naturalness of the sentence.

review sentences described in section 4.3 are generated from scenes and templates that agree emotionally.


Moreover, the examined blogs included 3 that were not identified using the emotion lexicons.

the E3 lexicons have different characteristic compared with the emotion lexicons.


The accuracy of 0.70 is not bad, however the E3 lexicons estimated 14 of 45; we obtained the recall of 0.31.

we can not say whether the E3 lexicons are good for estimating emotion, because the recall is low.


In this experiment, input information is one syntactic piece containing only two segments.


Tone recognition is difficult to incorporate into a phone recognizer (usually HMMbased model), because tone is a property of a syllable, not of an individual phone.

a lexical decoder or word hypothesizer is added to the system as a separate module in order to combine the output of the phone recognizer and that of the prosody processor together.


The labeling criteria provide a mechanism for mapping a sequence of acoustic correlates of prosody into abstract prosodic labels.

prosodically-labeled sentences contain information concerning the correspondence between the phonological and phonetic attributes of the prosodic structure of utterances and their intended meanings.


Given the strength dynamics as in the first sentence, the word /pet/ must have a label root because it has strength of DE, while the word /maak/ cannot have a label root based on the second constraint.

the compound interpretation is eliminated.


On the other hand, persistent clusters are seldom generated.

the algorithm is not the best way to observe topics continuously in terms of event tracking.


In other words, weighted words in a document reflect the trends at the time of its arrival.

scores in different documents may be different if the documents arrive at different times.


Our word weighting algorithm performs reasonably well only when the positive and negative regions of the differential curve are populated by existing documents; word scores calculated in the earlier period are not proper.

the articles prior to the last thirty days (about half of whole period) were not used for constructing the nearest-neighbor table, though all articles were processed to obtain trend scores during the last thirty days.


Therefore, the articles prior to the last thirty days (about half of whole period) were not used for constructing the nearest-neighbor table, though all articles were processed to obtain trend scores during the last thirty days.

567 articles (from the total of 1,037) were included in the nearest-neighbor table, and used for clustering.


In scoring words by IDF, the total number of documents and document frequency of words were updated each day by using articles up to the day because it is not feasible to obtain future given our assumption.


In that case, we often desire domain-specific knowledge for the system.

we need to efficiently extract sentiment sentences, which depend on a particular domain or topic.


The hierarchical attribute subsequence of the 2nd sentence in the figure is generated by skipping a node, Adverb.

the weight contains   Next, we compute a similarity between two HDAG structures.


In our layers, the word layer and compound noun layer are lower layer than the structural layer, i.e., the POS tag layer.

surface expressions are treated as important element in the case that 1 > β because the elements in deeper layers possess high weight values.


This result shows the importance of changing n in each step of the bootstrap approach.

we need to consider the determination of the appropriate n in each step.


To solve this problem, we applied a bootstrap approach to out method.

we acquired more sentiment sentences by adding the extracted sentences as new seeds.


However, even the recall rate with the bootstrap approach was insufficient.

we need to discuss solutions to the problem.


However, these values depended on the dataset in the experiment.

we need to consider an automatic determination method of these parameters to achieve higher accuracy for the bootstrap approach.


For the output selection, we compared each output in a preliminary exrperiment.

we obtained 4 effective features for the selection; (1) confidence, (2) the number of candidates, (3) existance of a short pause mark and (4) a similarity between outputs.


The DSSR often contained the short pause mark in the result in the case that an input was not an order utterance 1 .

the existance of the short pause mark in the output of the DSSR is effective to judge whether a input utterance is an order to the robot or not.


we obtained extremely high accuracy although the method was very simple.


It was decided, however, to consider all translations since the lexicon was built in such a way that the translations were all referring to a similar sense.

it should enhance the algorithm since it provided other possible translations for a single term projecting one sense.


From the results in the previous section it is clear that additional features are needed to improve the system's ability to tell actual antecedents apart from all potential candidates.

the first step in our present investigation was to extend the original set of features to gather as much information as possible about the anaphoric relations regardless of their usefulness to solve the problem at hand (which will be left to be 'learned' automatically.)


A possible reason why function_agreement was not useful in our previous work may be related to the excess of information that we attempted to convey as a single feature.

in the presently extended set of features this information is split into six separate features (namely, i_subject, i_direct, i_indirect, j_subject, j_direct and j_indirect), from which we expect to derive the required syntactic constraints as originally intended, whilst allowing each individual feature to influence the solution independently.


However, in the academic paper authoring setting, the scenario should be somewhat different, i.e., the users have all the different interests of their own.

it is almost impossible to enforce them to use only the allowed lexicon and not to use any words they like.


The authors write an English academic paper that will be automatically checked against Controlled Korean writing rules by a Controlled Korean Checker.

4 we investigated on the translation errors that might be occurred by stylistic errors that are hard for an MT system to treat properly.


Especially, in the academic paper authoring setting, it will be very difficult to train the users with the Controlled Korean.

the application of the above rules must be automated with a Controlled Korean Checker.


As the learnability is a very important factor for the acceptability by the users, we tried to formalize the Controlled Korean rules as much as possible.

we could improve the translation accuracy of the Korean-English MT system backed up by a Controlled Korean Checker for 4.25%.


Troubles has a higher score because it occurs more often in trouble reports.

we employed the method of Fujimura et al.


The evaluators classified 133 as trouble reports and 253 as no-trouble reports.

we used 133 trouble reports and 253 no-trouble reports as evaluation data.


In fact, ' ⇒ サポートに 電話する (call for support)' and ' ⇒ 画面が 表示されない(do not appear on the screen)' occur in the same reports.

if we connect Basis (2) and Basis (1), we can look on Basis (2) as belonging to Basis (1), with Basis (2) terms clarifying the meaning.


Basis (3) includes terms that cannot be considered troubles.

the rate of Basis (3) terms is higher than that of Basis (1) and (2).


In this paper, we provide alternative methods to cope with those problems within our user interaction environment.

authors can interact with the system through modification of source sentences, correction of engine errors, and correction of target sentence expression.


tepta 'hot, feel hot' and sulphuta 'sad, feel sad').

his suggestion is just another kind of typology of Korean adjectives based on the lexical meaning of predicates and not fundamentally different from what the previous researchers have suggested.


On the other hand, it is difficult to design a tag set (labels) that can be used to annotate a corpus because the design of a tag set depends on the domain and the task.

we have to redesign the tag set and construct a corpus annotated with a new tag set if we apply our system to different domains or tasks.


In addition, the feature space that is used to express any natural language expression is extremely large and an utterance is expressed by a very sparse vector in the feature space.

it is very important to handle a sparse feature vector of an utterance in the huge feature space.


An annotated corpus with DA is needed to construct our dialogue system.

we have started to design a DA tag set and annotate the DA tags on the corpus.


In that paper, Ohtake used PLSI and LDA to evaluate whether a paraphrasing pair is contextually independent or not, as well as if there was not a big difference in the performances between them.

we use PLSI because it is simpler and faster than LDA.


We can use regular expressions for pattern matching in a rule and we can conjugate any morphemes that have conjugation to fit in its context.

a small number of rules cover a large number of targets that need to be paraphrased.


The PLSI model can be regarded as a probabilistic version of a latent semantic analysis.

we can expect the same effect on PLSI, and we introduced the uni-gram and bi-gram features.


Finally, we compared each average vector with the others according to their cosine values, and we averaged the cosine values.

these numbers indicate the distinguishing ability of topic vectors, where a smaller number is better.


On the other hand, the original label "INFORM" indicated a miscellaneous category, and there were so many utterances labeled "INFORM."

utterances labeled "INFORM" were classified into many clusters.


So, we exclude the middle nodes in the outer coordinate structure overlapping with the middle nodes in the inner coordinate structure.

there are 4 CCSs in the example sentence as shown in the figure 4.


This kind of definition explicitly indicates the ontological hyponymy relation between 'dog' and 'Beijing dog' by using the concept 'dog' as the head sense.

the concept definition itself forms an ontological network.


For example, the passive '被 by' is a preposition that introduces an agent role/relation.

it indicates relations between constituents in a sentence.


The DOR is assumed to apply on the underlying level and explain the construction.

the DOR accounts for the transitive resultative in (3a) and the unaccusative construction in (3c) as well.


Nonetheless, the V2 fan in (24b) assigns its single θ-role to the object wo 'I', while in (24a) this θ-role is identified with that of V1.

the two θ-role identification patterns in (23) are equally possible.


Negative transfer of L1 features causes inaccuracies and errors in L2 speech productions, which impede intelligibility.

the study of L2 speech productions (i.e.


In a Chinese couplet, there is generally a direct one-to-one mapping between words at same position in the FS and SS, respectively.

the i th character/phrase in F is exactly "translated" into the i th character/phrase in S. Based on this rule, the phrase translation probability can be estimated by relative frequency in a training corpus: where m is the number of distinct phrases that can be mapped to the phrase i The inverted phrase translation model has been proven useful in previous SMT research work (Och and Ney, 2002); so we also include it in our phrase-based SMT model.


Although free text are more difficult to process comparing to well structured metadata, the structure of the articles in Wikipedia is in some degree homogeneous.

by exploiting this property, we can effectively extract relevant information from the article body as features.


As a characteristic of all encyclopedias, every entry in Wikipedia has a central topic, and does not contain much off-topic information, especially in the lead section.

the dominating pronoun type is likely to refer to the title.


Therefore, the dominating pronoun type is likely to refer to the title.

instead of resolve all pronouns in the article to find out which type of pronoun refers to the title, we took an alternative way of using a statistic method which simply counts redundancy and assume that the dominating pronouns (used over 50%) as referring to the title.


An underdeveloped entry may sometimes be removed due to policy issue or merged to an existing and well developed entry that has an overlapping topic.

unlike in the training stage, we exclude all stub or under-tagged articles at runtime for higher accuracy.


Nevertheless, web data is heterogeneous in nature and it is impossible to know the source information of the documents.

it is very difficult to do NER adaptation for web data.


Although some statistical RDR systems have been developed, such as the systems participating ACE, they were usually designed only for homogeneous data as most of the existing statistical NER systems.

most of the previous web text mining systems adopted rule-based approach to extract information (Rosenfeld et al., 2004;Soderland, 1999).


news) is more likely to be expressed by an emotion keyword.

it seems to be intuitive that emotion detection and classification is satisfactory if the collection of emotion vocabulary is comprehensive and an emotion taxonomy is given.


For example, in Chinese online chat, "雷(lei)" becomes popular to express "shock" emotion; 2) Emotion keywords often have multi-senses, and hence the problem of word ambiguity cannot be avoided; 3) Emotion context also has the problem of context shift as the sentiment shift (Polanyi and Zaenen, 2004).

even in formal text, emotion detection and classification is not a simple task, and it is a complicated job, which requires in-depth semantic understanding of texts.


The focus of our work is to explore the possible impact of emotion representations for emotion computing.


For example, "fear + anger" means this complex emotion is closer to "fear", whereas "anger + fear" means this complext emotion contains more of "anger".

in our LP system, we treat "fear + anger" vs. "anger + fear" as different tags, and there are totally 20 labels.


In (8b), x is accessible to z, but the identification of x with z is prevented by the Non-Identity Rule.

the construction rules of DDRT successfully account for why the intended coreferential reading in (1c) is not allowed, no matter whether every senator has scope over most representatives or not.


14 }, x will vote for z > In 14, where the quantifier most has scope over the universal quantifier every, the discourse referent introduced by the universal quantification phrase every senator is not accessible from the discourse referent introduced by the pronoun him.

the coreferential reading between every senator and him is not allowed, as is compatible with our intuition.


every x x likes y ⇒ <{ z male(z) pers(z) }, z will vote for y > In DRS (18), where the universal quantifier has wide scope over the conditional operator, the coreferential reading between every senator and he seems to be possible, just as in the case of DRS (15).

here again, we need to come up with a way to block the derivation from (16) to (18).


Symmetrically, it is unclear how various lexicon sizes impact the quality of the results.

we performed a series of experiments by training MElt f fr on various subcorpora and sublexicons.


The authors also report on a manual tagging experiment (without automatic pre-annotation); they observed an annotation speed that is around 1, 300 words per hour.

it is probably safe to assume that, on average, the creation of a manually validated training corpus starts at a speed that is around 1,000 words (30 sentences) per hour, and increases up to 3, 000 words (100 sentences) per hour once the corpus has reached, say, 5, 000 sentences.


The absolute difference of each paired rankings (D) was calculated and Table 4 presents the results.

based on D, the Spearman rank correlation coefficient r s was calculated between the automatic ranking of adjective density and human ranking according to the formula: the value of the Spearman rank correlation coefficient is 0.833, which is significant at the level of 0.02.


Based on the data from the training set, the regression equation is determined and graphed in Figure 2.

the acquired parameters are: α = 2.998 and β = 0.841.


The possible explanation is that the values of the expected rankings are in round numbers, when the actual values are 4.6 (unpublished writing), 4.9 (newspapers), 6.6 (non-academic prose) and 7.4 (academic prose) respectively.

although obtaining the same expected ranking number, those two paired sub-categories are placed in order.


We created our training and test sets by splitting the data for each verb into two parts: 70% for training and 30% for test.

there are 1300 sentences in the training set and 700 sentences in the test set, and each test set verb has been seen in the training set.


100 topics), the possible forms of topic space are huge, as well as embeddings of documents in it.

by regulating the topic space with label information, we should be able to find a topic space under which documents are linearly classifiable.


If we assume the variance of each category distribution is I, by removing the quadratic term exp(− 1 2z Tz ), p(y = k|z, µ 1:C , I) can be rewritten as It is the probability of logistic regression.


The identification of the head word of a phrase is not trivial, as SMT phrases are not restricted to linguistic phrases; simple linguistic rules of thumb cannot be used.

headwords of SMT phrases in a sentence are identified from the dependency tree generated for that sentence.


Once normalized, these weights can be seen as the posterior probabilities of the target phrases , k e which thus give access to P( k ê | k fˆ,DI( k fˆ)).

the expected feature is derived as in (7): In addition to the above feature, we derived a simple binary feature best ĥ .


We rewrite the optimization problems (7) in matrix form as shown below.

we first make equal conversion of (7) to obtain: we define a vector version of the single-parameter robust loss function M: the linear classifier optimization (3) can be rewritten as: The sum() function calculates the sum of all elements of a vector.


That is to say, the attempt of utilizing ASO features alone would deteriorate the overall performance as these errors might mislead the training of CRFs model.

a more wise strategy would be masking the errors and filtering out the beneficial part through feature combination.


Secondly, which may proves to be more crucial: the experiments conducted in (Ando and Zhang, 2005b) is based on semi-supervised learning, that is to say, a large amount of unlabeled data are involved to capture the common law inherent in the huge data set, which is then encoded in a common structure.

its effectiveness is based on information from a broad data span, which would be beneficial both for the precision and recall.


In this paper, three types of sentences, the first (firstS) and the last (lastS) sentence and the sentences with adverbs (advS), are considered to be more informative in determining the sentiment rating of a review.

at run-time, these sentences are given more weights by doubling the n-gram and semantic features therein while features of others not belonging to these three types are not duplicated.


One of the issues with respect to using KeyWords facility is the selection of the most appropriate reference corpus.

another goal of this paper is to test several possibilities for the selection of the appropriate reference corpus for key word analysis in terms of its size and composition.


It is obvious the selection of the appropriate reference corpus has much relevance to the results for key word search.


However, for some domains such as financial analysis very few annotated training corpora are available for mention detection.

in this paper we are more interested in investigating how much we can achieve on this task by only using the semantic knowledge discovered from Google n-grams, namely in a completely unsupervised learning framework.


In our approach, the contrary is true -the extremely large n-grams provide us high coverage of candidate mentions but at the same time bring a lot of noise.

we need to explore various effective confidence estimation metrics in order to separate the "wheat" from the "chaff".


They make decisions at a configuration which is usually composed by a couple of focus tokens and the parsing contexts.

these two kinds of dependency parsing methods represent the two extremes when they seek the best dependency structure of the input sentence.


sVMs were used for both our English and Chinese experiments.


However, these opposing statements may coexist under certain situations, and presenting such situations is helpful for a user's judgment.

we focus on the coexistence of these opposing statements, and attempt to develop a system to generate survey reports that contain mediatory summaries, which are defined as passages extracted from Web documents in order to present situations in which these opposing statements can coexist.


Many pages on the Web contain incorrect or unverifiable information.

there is a growing demand for technologies that enable us to obtain reliable information.


Although using similarity guarantees that a value flowed out from a vertex is equal to the one flowed into the vertex, using uniqueness does not guarantee it.

scores of vertexes are normalized by dividing them by the sum of scores of all vertexes in a graph.


However, increasing the weight of reason link can improve results in such topic.

the proposed method based on the multi-layer network in which reason relations are introduced is effective for extraction of significant passages that do not include frequent words.


The most refined typology of LDAs to date that also incorporates the core-exempt distinction is Cole, Hermon andHuang (2001, 2006).

we will attempt to interpret the results of the empirical study in light of the proposal made by these researchers.


However, the directional auxiliary o-ta 'come' in the adjunct clause implies that the matrix subject Yenghi is the deictic center, as Chelswu is described as coming toward her.


local and LD binding)-as long as an antecedent is there which c-commands it, which is also falsified through the results of the experiment.


However the narrow(est) scope requirement is defined in the lexical entries of the head Ns (relational nouns).

the free variable, which should be bound by higher quantified phrases which the relational nouns scopally depend on, must be present throughout the interpretation process.


On the other hand, relational nouns must be defined as Skolem terms from the beginning (defined in the -terms).

the corresponding -terms contain free variables inside the terms, which cannot disappear throughout the interpretation process.


Oddly enough, though, the variations seem to be impoverished compared to the outputs of well-constrained (lexicalized) grammars.

the combination of the conservativeness and allowance for endless variations defines what I call "bounded productivity/creativity under conservativeness" in natural language production, by which This implies that, on the one hand, productivity of natural language is constrained under strong tendency for conservativeness, and on the other hand, there are endless variations of expressions.


The VMT runs counter to the fact, in the sense that remembering something in a vast memory is like "finding a needle in a huge hay stack."

the real challenge for the VMT is not the issue of memory limit, but the issue of unexplained efficiency with which records are retrieved or recalled.


The rank of patterns is defined as follows: In a PL constructed for an array with k-segments, the number of constants in a pattern corresponds to its rank.

the null pattern at the top is always at rank 0.


Lexical patterns are always more remote from the fully lexicalized instances than the superlexical ones and are allowed only indirect contributions to the overall interpretation of a given sentence.

"superlexical" semantics supersedes the "lexical" semantics.


This is because under PL, patterns, lexical or superlexical, are just indices for instances, and they do not (need to) have meanings of their own.

it can be argued that they appear to have meanings of their own just because they serve as "keys" to full instances that bear meanings.


In machine learning approach, a document (text) is usually modeled as a bag-of-words, a set of words without any word order or syntactic relation information.

the whole sentimental orientation is highly influenced by the sentiment polarity of each word.


The sentiment polarity of the word good in these two sentences is positive but the whole sentences are negative.

we can see that the whole sentiment is not necessarily the sum of the parts (Turney, 2002).


We then partition them into two groups: one includes those called sentiment-reversed sentences and the other includes those called sentiment-non-reversed sentences.

each document is represented as two-bags-ofwords rather than traditional one-bag-of-words.


But their sentiment polarities are obviously different from each other.

traditional bag-ofwords modeling is not appropriate for sentiment classification to some extent.


Since the sentences in the sentiment-reversed part are possibly expressing the reversed polarities, we would like to shift the parameters ˆn w when they are applied to the sentiment-reversed text.

the label Y ′ of one sample where N re X − ′ represents the input vector of the sentiment-reversed text.


The results in some previous work are sometimes not consistent due to the application of different domains of reviews when negation is considered (Pang et al., 2002 andNa et al., 2004).


But the improved performances in some domains are insignificant (less than 0.5% in camera).

it is not strange that the conclusions in Pang et al.


L and Λ are the labelling and inverse labelling functions.

dA sequences until turn t only affect the first t turns in the dialogue (i.e., Pr(W the terms in the product in Equation 2 are rewritten as: This model in Equation 3 can be simplified with some assumptions: the current dA depends only on the previous n − 1 dA and the sequence of words of the current segment depends only on the current dA.


The search problem given by this model (the search for the segmentation and DA sequence with maximum probability) is solved using the Viterbi process, which implies that the summation is changed by a maximisation.

the final model is: Following the work of other authors (Stolcke et al., 2000;Young, 2000), the terms in Equation 4 are modelled as follows: Pr(u k |u k−1 k−n+1 ) is usually represented by a statistical model of DA sequences (DA language model), generally an n-gram model, and Pr(w s k s k−1 +1 |u k ) is usually modelled by a HMM.


The alignments between the words in the turn and the corresponding DA labels are monotonic (no cross-inverted alignments are possible), and consequently no conversion to SFST is necessary to efficiently apply a search algorithm on the n-gram.

this n-gram acts as a transducer and gives the name to the technique (NGT: N-Gram Transducers) (Martínez-Hinarejos et al., 2008).


This difference is due to the nature of the corpus: Dihana is a task-oriented corpus with a limited number of scenarios; this causes dependencies between the DA sequences that are captured by the DA language model.

the DA language model degree has a higher influence in the annotation and segmentation.


This n-gram can be used directly in a speech recognition system as language model, producing a DA annotated recognition.

future work is directed to include this annotation model into a speech recognition system.


On the other hand, different words (e.g., plant and factory) may express very similar meanings (e.g., the working place for industrial labors).

wordNet (Miller et al., 1990), a sense inventory encoding with semantic relatedness of words, has been a valuable resource in the field of natural language processing since its introduction.


Following describes three types of literal features for Chinese translations: Unigram Feature: Chinese characters tend to carry some sort of semantic meanings.

we split Chinese translations into characters and collect their corresponding features.


Head Word Feature: The head word of a Chinese translation may occur at the beginning or in the end and the length of a head is uncertain.

both ends of the translation and a preset character limit on head word are used to generate our head word features.


Similarly, Tokyo-no shinseki "a relative in Tokyo" need not imply that the relative was born in Tokyo; it probably implies he currently resides in Tokyo.

the AGENTIVE role modification is not relevant.


The lexical input for shinseki "relative" in GL should not allow modification by a locative genitive phrase Tokyo-no "in Tokyo" under the existing GL, since Tokyo-no "in Tokyo" would not modify any inherent qualia roles.

3 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 5 we incorporate location as part of the referential or extensional module (EXT) such that the location of a relative can be modified by the locative postpositional phrase as in (22).


With regard to the sentences with  and with Mari-no koto-o 'Mary's matter' in (20a), they are synonymous, although it seems that the latter is a more indirect way of expressing what the former means.

we conclude that o in (19) is the contraction of no koto-o in (20a).


Pseudogapping occurs not only in coordination structures, but in comparative or subordination structures.

this paper introduces a pseudogapping schema that can be applied to all structures mentioned above.


And the latter has its own MODE value, INDEX value, and non-empty RESTR.

this indicates that argument-marking prepositions are transparent and can be elided with verb, while predicative prepositions are non-transparent and cannot be elided with verb.


However, pseudogapping also occurs in subordination or comparative structures, as in (2) and (3).

in order to cover as many as phenomena, the pseudogapping schema which can be applied to any structure is needed.


Pseudogapping is a peculiar phenomenon related to semantics as well as syntax.

we have to investigate how people can process the sentences with pseudogapping.


Although clitic elements abound in Korean (Kuh 1988, Chae & No 1998, Chae 2005, Chae 2007, traditional approaches have not given due attention to their existence.

many (clitic) words have not been considered as head words.


It is supposed to tell the color of what thing or who so that people can understand the expression.

the attribute noun "颜色(color)" can not be isolate subject in sentence like noun "今天(today)".


Attribute nouns with different meanings calls for predicates that with different concept.

we can assign an attribute noun to more specific ANC class in terms of the meanings of predicate collocated with.


There are two meanings of attribute: 1) the value of attribute (昂贵/a 的 价格/h, high price) which semantically resembles the predicate in 2.2.1; 2) the host which semantically possess the attribute (书/a 的 价格/h, price of the book).

the meanings of host of attribute and attribute, as well as attribute value and attribute should match each other.


The attribute nouns can be assigned to more specific ANC classes in terms of the meanings of words with which the attribute nouns collocate in SP, VO and AH.

the selectional restrictions in three grammatical relations can be used as subcategorization criterion for ANC.


The structure presentation of these nouns is: Thus we create a new ANC subcategory for the two nouns: "appearance attribute of human".

the verbs of noun "意图(intention)" are of meaning of "mental processing", so it can be presented as: we generate a subcategory for it: "mental attribute of human".


Naïve Bayes and Naïve Bayes Multinominal Classifiers were used to evaluate the performance of the proposed feature set in terms of F-score.

of the experiment, the linguistically rich POS set demonstrated superior classification accuracy when compared with a bag of words and linguistically impoverished tags.


We hypothesize that the reliability of prediction of each classifier differs among the various output classes.

it is necessary to find out the subset of classes for which any particular classifier is most suitable.


Moreover, all the classifiers are not equally good to detect all types of output classes.

in a voted system, a particular classifier should only be allowed to vote for that output class for which it performs good.


However, we did not find an interaction between rhetorical distance and working memory group.

our results supported the Separate Language Interpretation Resource theory of working memory structure (Caplan and Waters 1999).


Caplan and Waters (1999) replicated the experiment but did not find the required interactions.

they interpreted their results as supporting the SLIR theory.


As shown in table 3, the percentage of correct answers to the fact questions did not declined with the increase of rhetorical distance and the corresponding decrease of AS.

we can assume that there is a separate module of WM dealing with the reference processes.


However, we did not obtained the main effect of an interaction between rhetorical distance (RhD = 1, RhD = 2, RhD = 3) and WM group (high, medium and low span).

we can interpret our results as supporting the SLIR theory.


Under the PIC, a phase edge remains visible to a higher phase.

there is an apparent imperfection -the lack of a one-to-one correspondence between sending an element off to Spell-Out and phase-hood.


This means that an EPP feature must be present in every phase head that intervenes between the base and scope positions of a wh-phrase in constructions such as (2-3a).

v* must have an EPP feature, as shown in (2b-3b), that attracts the wh/Q-element to the v*P edge (copies of moved phrases are italicized).


A subject contains an unvalued '[Case: ]' feature.

the EPP subfeature forces a subject, assuming that it is base generated at the edge of a v* phrase, to undergo movement (leave a copy in its base position) and Merge again with T. We assume a bare phrase structure (Chomsky, 1995a) view of a syntactic tree, as in (6).


For example, in 7, when C* is Merged, the lower v* phase is sent to Spell-Out.

v* and anything contained within it (that has not already been sent to Spell-Out) is accessible to higher operations up until C* is Merged.


The selected element N is the label of the constituent, and this label contains a '[+WH:X]' feature.

in accord with (13a), the Selector searches in the subnumeration for an element with a matching unvalued feature.


Feature checking applies, and in accord with 16a As discussed in section 2, we assume that when a phase head is Merged, a lower phase, if present, is sent to Spell-Out.

as soon as the phase head C* is Merged (20), the lower v* phase is sent to Spell-Out.


This root noun is turned into an agent noun by the attachment of -er.

philosoph depends on -er, and as a result the chain mor-al philosoph depends on -er.


In 30, the noun friend is changed into an adjective by the attachment of -ly.


The attachment of -er transforms hang into an agent noun.


It will also happen for the global optimum and may result in disruption of the near-optimal solutions.

gA will never converge to the global optimum.


Elitism is implemented at each generation by preserving the best string seen up to that generation in a location outside the population.

on termination, this location contains the best feature combination.


Shahmukhi is a variant of the Perso-Arabic scripts.

it possesses most of their inherent characteristics such as right to left writing, an optional use of diacritic marks and short vowels being not considered as letters of their own but applied above or below a consonant by using appropriate diacritics.


In contrast, conjunct and compound verbs can only be identified by the analysis of multiple words and mostly have a semantic role.


Although much research has applied dependency grammars for reducing the complexity of sentences to match the characteristics of Korean (Kim and Lee, 2005;Nam et al., 2008), this has still caused problems which prohibited wide use.

we suggest a new morphological chunking method that binds semantically related concatenations of morphemes.


The negation shifter 없 eps 'no' affects the value of 흠 hum and then, the value of 흠 hum is changed to positive +1.

the total value of example (3) properly reflects the positive meaning of the phrase 'The person who has no fault'.


In the simple classification which does not use information of chunking structure, a [-2, +2] window determines the influential scope of functional items.

the negation shifter 않 anh 'not' cannot change the value of 해결 haykyel at -3 position and the value of 해결 haykyel incorrectly maintains as positive.


This verb is treated as one single item in a chunk and is included in the same chunk with the negation shifter 않 anh.

the influential scope of the negation shifter can cover the noun 해결 haykyel and then, the value of 해결 haykyel becomes -1 by multiplying by -1.


News articles have no marks representing subjectivity or polarity of sentences compared to the grading systems found in movie review texts.

in our work, two native Korean annotators manually attached polarity labels to each sentence.


It becomes possible because the future reference time can be established from the context.

a simple ø-marked PRES with -te cannot guarantee direct evidence.


(15e) cannot modify the embedded S. The need for such a complex S analysis is further shown by the following psychological adjective, which requires an Equi-Subject constraint by subjectification: In the underlying structure (13a), the subject of the embedded complement clause pro must be co-referential with the subject of the higher verb of saying; the speaker alone feels dizzy at speech time in Korean.

the surface subject of (16) is the source (speaker) of the report content and the Experiencer of feeling dizzy.


So far these have not been treated together.

the declarative reportative -tanta form also comes from -ta-n-ta <[[----ta-ko] ha-n-ta] (see the deletion and contraction steps in (15) with -n: PRES, -ta: DEC in the matrix sentence).


That is, onset and nucleus form a core and that this core combines with coda in order to form a syllable in our implementations.

the rules for these types are necessary.


One is the structure where syllable includes only core (the case where syllable contains no coda), and the other is the structure which is composed of two constituents, core and coda.

two different types of rules have to be made separately for the type syllable.


In the actual syllabification, however, the left syllable structure is correct for the word 'nala'.

it is necessary to make the right syllable structure not generated during the parsing processes.


Because the CV structure is more preferable than the CVC one, the left syllable structure is preferred to the right syllable one.

the parser correctly selects the left syllable structure for the word 'nala'.


Crosslinguistically and in Korean, focus is more frequently associated with objects than subjects but is a rare and unexpected property for subjects.

fine-grained differences within the category of focus in relative predictability are more important for marking of objects and less important for that of subjects.


Our eSpaceML, on the other hand, simply refers to ISO-TimeML (ISO, 2009c) and some other necessary and available annotation schemes, as shown in the central circle of Figure 1.

eSpaceML does not have those two tags in ISO-Space, namely <STATE_LOCATION> and <MOTION_TRANSITION>, which anchor events to locations or paths.


Second, it distributes various parts of the task that ISO-Space undertakes in two different ways: one is to distribute the task to other available annotation schemes such as ISO-TimeML that links events to time and the other is to relegate fine-grained semantic issues to formal semantics that treats inferences as well as logical reasoning.

eSpaceML becomes a compact representation scheme for spatial annotation proper.


Digital data elements that are extant and discoverable are still not useful if they are not accessible by parties who need them.

data elements in a repository must have clear access policies and clear addressing.


Textual corpora are not only useful for linguistic research purposes, but also serve as recordings of cultural heritage.

in designing a corpora repository, especially for rare resources of certain languages, one must consider that the digital representation will still be interpretable, say, a hundred years into the future.


For example, a corpus of texts originally collected by a computational linguist, who added POS tags and constituent bracketing, could subsequently be used by a sociolinguist, who then adds annotations concerning register and social context factors.

one key design consideration is that primary data can be made available for reuse by many communities of researchers.


The vocabulary of the medium-scale DSSR is the union of each small-scale DSSR.

the multiple speech recognizer consists of one LVCSR, one medium-scale DSSR and some small-scale DSSRs.


However, it needs to handle spontaneous speech utterances.

the grammar file consisted of the combination of the words in a fixed length; e.g., Noun-PP-Noun-PP-Verb.


Besides, we verified that the change of the F-value was small even if we changed the thresholds within the compass of 0.20-0.26 2 .

our method, which was based on the edit distance, for the output selection in a multiple recognizer is simple and robust.


The emphasis aims at convincing the hearer or reader of the effectiveness of an advertised product.

the emphatic context pragmatically licenses the appearance of the resultative predicate dead after kill.


To insure the attainment of the goal, Chinese uses resultative verb compounds in which the first element denotes an action and the second one the result.

we can say that the implication in the Chinese verbs in question emerges from the composite meaning of the whole resultative verb compound or from the context.


On the other hand, shā merely implies that the patient dies as a result of the agent's action.

it can be confirmed as in (5) and cancelled as in (6).


The SELC Model is built based on a lexicon-based approach.


In this model, verbs describe events or states and arguments are associated with their verbs via secondary predicates that denote general thematic relationships, like "agent-of"' "theme-of", etc.

action verbs, such as sing and dance, are relational, containing an extra argument place for an event e, as shown in examples (14a ,b) and example (15) can be rendered as shown in example (15').


Therefore, it is natural that the event structure of "V-te-a-ru" constructions requires the temporal restriction between the two sub-events.

example (2) can be expressed as example (16), where ("e < e' means that e precedes e'): (2) Mado-ga ake-te-a-ru.


The truth conditions of example (2) require an event of opening, whose agent is not given, whose theme is a window, and an existence of an (open) window, but no further relationship between the event and the state is mandated.

beyond sharing the common entity "mado," window, the culmination of an event and the holding of an actual state need to be linked by relativizing them to time.


However, they have one significant peculiarity: it can take the topic qua experiencer in the experiential sub-event.

as shown in the above section, at the semantic level, the experiencer (which can be considered the topic) is also an agent causing the sub-event: the agentive process of sleeping causes the experiencer to enter an actual physical state.


17 Here too, we must note that the causing sub-event temporally precedes the resulting sub-event.

the temporal order of the two sub-events is restricted: the agentive process causes the experiencer to maintain an actual physical state.


Term extraction aims to extract meaningful words or phrases representing domain specific meaning or concepts.

two issues are considered in term extraction.


The proposed FTL approach extracts terms using automatically generated seeds instead of domain knowledge or annotated corpora.

it is applicable to any domain specific corpus.


Fault-Tolerant Learning proposed in this study makes use of seeds produced by unsupervised techniques without manual checking.

noise may exist from the beginning and could increase after each iteration.


Many domain specific terms are descriptive and very long.

pOS may provide useful evidence about the term boundaries.


Candidates with certain head words or end words are more likely to be certain kinds of terms.

the statistical information of head words and end words are collected to distinguish terms from non-terms.


DList obtained from training data is proved to perform better than a stop word list.

training data are used to guarantee the best performance of the reference algorithm.


Moreover, FTL requires no prior domain knowledge and no training data.

it can be applied to different domains much more easily than traditional supervised methods or domain knowledge based algorithms.


There are also views which although compatible with the demonstrative and quantificational positions, present complex demonstratives in a different light.

roberts (2002) claims that they are just definites.


Another way to do this is by modification, that is by successive application of one or many modifiers to a specific argument.

we can apply a simple adverb to a verb phrase, possibly complex (e.g., resulting already from a Boolean operation) to obtain by modification a more complex verb phrase.


One observes first that there are simple Boolean compounds of this demonstrative.

we have this and this, this or this, this but not this.


We also notice that such Boolean compounds of "pure demonstratives" can Booleanly combine with non demonstrative NPs to hold syntactically complex (demonstrative) NPs .

we have Leo and this, (as in I hate Leo and this), Lea but not this, some logicians but not this, most philosophers but not this one, this but not this neither most dogs, this but no artichoke, between six and ten Latin letters but not this, etc.


In opposition to this the complex noun phrase demonstratives we consider have only one common noun as argument.

we observe that the Det and this in examples we consider must apply to the same common noun.


Ignoring various scopal possibilities of intelligent and ambiguity of young we can consider, given the property of freely increasable domain of quantification indicated above, that (4a) is logically equivalent to (4b), (4c), (4d) and 4e Furthermore, we observe that (4a), and as a matter of fact all sentences in (4), entail (5), which we consider for purposes of illustration, as grammatical: (5) This is intelligent This series of equivalences allows me to be mistaken as to the property by which I (partially) describe the object pointed at when using the specific noun phrase demonstrative.

it can happen that I am pointing at something which is a wild cat but not a young wild cat.


Thus we cannot in general find a property P such that (7a) is equivalent to (7b): (7a) Most wild young cats, including this one, are intelligent.

(7b) Most beings, including this one, are intelligent and P. my mistakes in the description of demonstrated objects are different when I use (syntactically complex) demonstratives denoting sortally reducible quantifiers than when I use demonstratives denoting sortally irreducible quantifiers(in subject position) .


This can be explained by the fact that in character-level SMT models observe all possible characters of the language when a reasonable amount of example-base is used to train the system.

the character-based system produces transliterations for all the NEs and no back-off is being taken from the AEBMT system.


In contrast, in Japanese complex sentences the adverbial clause must precede the main clause.

in Japanese only 'Before1' and 'After1' sentences are permitted (Sasanuma & Kamio 1976).


Hence, sentences with 'Main-Sub' order are more difficult for understanding than sentences with 'Sub-Main' order.

we predict Russian counterparts of (1a, c) sentences to elicit less errors than those of (1b,d).


Also, although the IBM2-based models did not outperform HMM entirely, for many language pairs the difference was estimated as insignificant and for some others -significant but relatively small.

the relative distortion-based IBM2 models can serve as an efficient trade-off between efficiency and quality.


It tries to always relate golden nuggets found in corpora to the context of their original data source.

it involves more an interaction with corpora than a distillation process of them.


Although a suite of heuristical methods are presented for word sense disambiguation of Chinese Wordnet glosses, unfortunately we know of several researchers who use only manual analysis to find out the argumentative roles and predict their semantic features to determine their senses.

they can't deal with more quantities of lexically ambiguous words at the same time.


Lexical ambiguity means some words have multiple meanings or senses (Moldovan and Novischi, 2004).

the first hypothesis is that words with similar morpheme-character components and concept elements are similar in sense.


In general, observations show that high-frequency words are usually highly ambiguous and have more senses; on the contrary, low-frequency words usually have less senses or only a single sense.

we attempt to examine these peripheral words individually for these four target words and their frequencies are similar in Taiwan's Central News Agency of Gigaword Corpus and these words have analyzed in Chinese Wordnet already.


However, some texts in a book like interviews and essays include colloquial expressions.

we introduce two degree of a colloquial style.


However, finding typical examples itself is a difficult task.


, c n in parse p = with anchor a is carried out in such a way that constant c i is replaced by a grammatical role/function that is defined relative to a.

p1: "Ann gave Bill a hug" is rendered into the sequence "Ann V O1 D O2" because gave, Bill, a and hug bear the roles of verb (V), direct object (O1), determiner (D) for O2, and indirect object (O2) relative to Ann.


This is because it is moved to a [+WH] COMP; the movement is hence wh-movement.

takahashi's (1993:660)  to the extent that the interpretive difference between (15a) and (19b) on the one hand, where reconstruction is possible, and (16a) and (19c) on the other hand, where reconstruction is impossible, can be captured by the distinction between wh-movement (for the latter) and scrambling (for the former), and inasmuch as the lack of reconstruction for long-distance displaced wh-phrases in cases like (16a) and (19c) can be assimilated to the scope property of the wh-moved phrase in English in (17a), the case for treating long distance displacement of whphrases in Japanese as overt wh-movement may seem prima facie strong.


Major differences are in the treatment of modifiers and long-distance dependencies.

we need the preprocessing of the XML output for these constructions.


M will be inapplicable at the last level.

the correct generalizations are captured again.


The refinement of the verb classification in Section 3.1 and 3.2 contributes to eliminate the redundancy between argument structure and lexical semantics.

hPSG's multi-dimensional constraint-based architecture is well-suited for representing linguistic information which ineracts with syntax, semantics and pragmatics in principled ways.


It explicitly expresses information providers' specification for the information sources and their attitudes toward the information by the use of evidential.

evidentiality could be an explicit cue for the information quality in CQA answers.


However, the results of voting would not be revealed to the community until the voting period is over.

waiting for the voting results is sometimes a long process.


Other N-gram models have also been shown to be very effective for many text processing applications.

we would like to check the effect of these N-gram models for our CQA task.


As already mentioned, the whole process of the annotation is computer-aided, i. e. with extensive exploitation of available NLP tools and resources for Czech.

as side effects of the annotation, we will gain improvements of these tools and resources by investigating differences between their output and the annotation and fixing errors on the right places.


Much debate has arisen over Talmy's (2000 a&b) typology, and several questions concerning how and where languages should be classified have surfaced.

it was crucial to look into the research backing the classification of English, Japanese and Chinese before beginning this study.


A friend of mine likes DRT on Mondays and Thursdays and hates it on Tuesdays and Fridays.

14Ta jintian zenme zheme congming le he today why so clever SFAP Lit: it seems that he becomes much smarter today this paper adopts Chierchia's (1995) porposal of viewing both stage-level and individuallevel predicates as Davidsonian in which an external argument for space-time locations will take effect on the process of topicalization, besides other normal thematic arguments.


However, with regard to discovering potential novel terms for terminology lexicon editors, CRF model fails to show good performance, if trained with known term list only to predict novel terms in testing corpus.

this result suggests that more semantic information may be needed to determine a word to be a novel term during a specific period.


And "in selecting the expressions to be used for a new MeSH descriptor, it is the usual practice to adopt the expression most commonly used by the authors writing in the English language."

novel terms may not only refer to those new words that are newly created and specifically for some meaning in a certain domain, but also could be some known word whose meaning is changed from the common understanding to be specialized in some domain.


Also, the testing set contains one subset of corpus.

the training to testing ratio of training set 1 over testing set is 1 to 1 and of training set 2 is 2 to 1, and of training set 3 is 3 to 1.


Likewise, the other training sets have corresponding training and testing ratios.

the training to testing corpora ratio of training set 1 to training set 8 is increased from 1 to 1 to 8 to 1.


When testing, the CRF framework will tag 1 to a word in a matrix if it determines the word to be a MeSH term, and 0 otherwise.

the precision of it is the ratio of the number of correctly determined terms to the number of terms it tags as MeSH terms, and Recall is the ratio of the number of correctly determined terms to the number of true MeSH terms in this testing corpora.


As introduced earlier, the final objective of this study is to generate a novel term candidate list for human experts to discover novel terms.

a novel term candidate list is generated.


After testing, CRF framework will have tagged 1 or 0 to a token in a matrix if it judges this token be MeSH term or not.

all these tokens tagged as 1 are terms recognized by CRF.


Currently in the Modern Standard Arabic (MSA), diacritics are omitted from written text almost all the time.

this omission increases the number homographs (words with the same writing form).


As a final point, different orthographic conventions exist across the Arab world (Buckwalter, 2004a).

of omitting diacritics, complex morphology and peculiar orthographical rules, processing Arabic text is a difficult task whether performed using statistical or rule-based methods.


Running AMIRA 2.0 to tokenize such a huge corpus is a time consuming task.


space marks are used as the explicit delimiters or token separator.


Being a benchmark study on NLP, the developed lexicon is useful for spellcheckers in Tagalog and for other users of Tagalog language and its application.

autoLex is capable of automatically building a lexicon for spelling checkers.


Sometimes, the comments of one blogger are annotated by other bloggers in the blog posts.

the holder annotation task in user comments sections was less cumbersome than annotating the holders inscribed in the topic section.


In other words, it is more possible to disrupt communications by TYPE II submissions than TYPE I.

in this study, we intend to investigate a method of detecting users who have repeated TYPE II submissions.


In this way, the key to detecting users of similar writing styles is the user classifiers.

we explain below how to develop these user classifiers.


However " (stupid)" in (b) means " (very)" which is used just for emphasis.

detection is difficult because we need to consider the neighboring words.


Furthermore, a Japanese morpheme analyzer cannot segment the words of BBS posts correctly because they contain several coined words.

we cannot correctly detect them that are segmented, so nasty words cannot be registered sufficiently.


Building seeds dictionary of nasty words   Many nasty comments are necessary to make n-gram model, but it is very expensive to extract them manually from many comments.

we first extracted nasty keywords manually from the BBS posts and then built a small dictionary.


We judged that the detection was insufficient because there were only a few variations of nasty comments seen in our comment collection.

of our continued collection of comments from 2ch using the small dictionary, we obtained approximately 200,000 nasty comments.


They experimented on six patterns of feature combination with the SVM.

they described the highest accuracy using a combination of the features of Term Frequency -Inverse Document Frequency (TF-IDF) and Chi-square.


A dictionary including such notational variants is extremely useful in many cases such as normalization of word expressions in information retrieval and normalization of word expressions in text mining or information extraction.

we studied the automatic extraction of the notational variants of a Japanese word.


We made from them word pairs where the first word and the second word in a pair were exchanged.


In our experiments, we found that there were no features where the elimination of each of the features was significantly better than the use of all the features in both Experiments A and B at the  Table 6: Acquired patterns Acquired pattern Notational variant pairs " delete" " " (sio ko syo u/sio ko syo u) (salt and pepper) " (ru) " " " (ha ru ma ge do n/ha a ma ge do n) (Armageddon) " "(ko) " " (hi ki ko mo ri/hi ki ko mo ri) (withdrawal) significance level of 0.05 by a bootstrapping method.

we found that all the features we used in this study were useful and we had better use all the features.


Finally, we applied our method extracting a notational variant pair described in Section 4.

we obtained 4.2 million word pairs as notational variant pairs.


We found that 233 pairs among the 300 pairs (78%) were correct.

the extracted pairs would include 3.3 (= 4.2 × 0.78) million correct notational variant pairs.


If an activity verb appears within the relative clause, it is a spatio-temporally co-occurring argument.

in this case, the event of the relative clause and that of the main clause must have a point of spatial or temporal overlap.


This change may occur differently with same endings.

nouns are categorized to define inflection rules.


Reversible nature of FSTs makes it possible to execute the whole process of mapping lexicon to surface levels in reverse order.

noun inflection FSTs discussed here are not only useful in inflected word formation but also in morphological analysis/parsing of Sindhi nouns.


What we found was that the resultative -ko iss-was not explained explicitly as a particular function of grammar, and was exposed only through lexical expressions that described clothes with wearing verbs.

it is safe to presume that the overall accuracy rate of the resultative -ko iss-increased significantly due to L1 transfer and being triggered by focus-on-form teaching.


Although handling these information (evaluative information) has become necessary, there exists too much information on the Web.

extracting information that users want and summarizing them have been expected recently.


We need to handle redundant information regarding as a feature to determine an important sentence.

we aim to integrate similar opinions by clustering them.


In the algorithm mentioned above, each cluster is formed with evaluative sentences which are gathered by co-occurrence of some words.

each cluster contains words which appear in common in the cluster.


For example, the co-occurring words of the nouns from an input document can include the content of the document.

we can use the co-occurring words as correct data items in criterion (ii).


The candidate score of shuushoku katsudo (job hunting)was the highest.

the system outputted shuushoku katsudo (job hunting) as the summary for the input document.


By letting the last reading of a given type survive even in the presence of input constructions the grammar was not designed to handle, a CG system achieves a certain robustness, and all text will be analyses.

the English CG we were using for our annotation task, though in principle designed for written text of the news and scholarly genre, can also produce annotations for data of varying degrees of what we will call orality 1 in this paper -text with a certain amount of features typical of spoken language.


Safe rules typically ask for unambiguous contexts, therefore rule batches need to be repeated so less heuristic rules can be retried once their context has become a little less ambiguous due to other rules.

for the 6 heuristicity levels in the morphological disambiguation CG, batch order will be 1 -2 -1 -2 -3 -1 -2 -3 -4 -1 -2 -3 -4 -5 -1 -2 -3 -4 -5 -6 -1 -2 -3 -4 -5 -6, with 1 being the safest and 6 the most heuristic level.


However, the chat corpus scores much more consistently along the complexity axis than the e-mail corpus and Europarl.

the chat corpus has the highest occurrence of interjections 5 and pronouns, and the lowest score for verb chain length (auxiliaries), as well as for subordination, infinitive/participle subclauses and would/should distancing.


The Europarl corpus, in particular, is atypical for speech, and in many regards closer to running text, most likely a consequence of it consisting of formal monologue, with an abstract public in mind rather than an individual turn-taker.

the Europarl data boasts the longest words and longest sentences 6 , and scores highest for subordination and infinitive subclauses, as well as the rare past participle subclauses, all of which considerably complicate syntactic trees.


Since all its elements are identical, the least-frequency property is preserved, even if the matching simply starts on the left end, or alternatively on the right end, and continues as long as new matches are found.

iteration elements can itself become part of complex queries, and the three operations Q: x , ⊕ and establish a query language with the power of regular expressions, over an annotated text with any number of annotation layers.


We extended the CQL formalism in a way that enables a meet/union query to be placed at any position in the standard query syntax.

we can exploit both the extended meet/union and within/containing queries to make a contextual search for e. g. all sentences where the verb have occurs in a −5 to +5 context of a pronoun and concurrently some noun occurs in a −3 to +3 context of the adjective blue: 6 Parsed Corpora Our larger corpora do not currently contain phrase structure or similar markup, and for this reason the paper focuses on queries which do not assume it.


Nevertheless, there will be differences with respect to morphosyntactic categories that do not exist in all the languages.

we expect all the five languages to have nouns and verbs, for example, but not four case distinctions.


The dataset of each database has its own specific enrichment and has been tagged with parts of speech tags that differ per database.

these tags may vary from one database to the other.


Important potential synergies for the research of both parties have consequently been neglected.

as well as extending our tools in the ways already outlined, we are promoting them by demonstrating the benefits of corpus use in research and teaching at workshops and departmental seminars across the humanities.


Entering full-fledged CQP queries for multi-word searches and complex patterns is usually beyond the skills of students or researchers in the humanities.

we have implemented the intuitive query builder interface shown in Figure 2.


However, a major problem, highlighted by language learners and tutors alike, is that students often find it hard to understand the language written in the concordance lines; most corpora were not built with the language learner in mind and are made up of authentic texts of various genres and therefore no attention has gone into selecting texts of an "appropriate" level.

students at the beginner and (lower-)intermediate level have been highly restricted in what they can use corpora for.


Unlike "hard rules" at morphological and syntactic levels, many discourse phenomena are usually governed by "principles" or "preferences."

it is hard to provide explicit and systematic instructions.


McCarthy, 1991), it is undeniable that a focus on sentence-level form tends to be emphasized in many foreign language teaching contexts.

it is crucial to develop effective ways for learners to better understand the concept of discourse coherence and to utilize relevant cohesive devices.


In other words, the texts that the project participants have themselves produced will be used as a resource for teachers and learners in their own classrooms.

the compiled corpus is not intended for public distribution.


People are fascinated and influenced by touch screen and various software(s) installation facilities on these new generation gadgets.

lexicon level polarity assignment is bit difficult.


SentiWordNet is an automatically constructed lexical resource for English that assigns a positivity score and a negativity score to each WordNet synset.

we decided to develop SentiWordNet for new languages.


Moreover sentiment is a social understanding which we, the human being learn from the society by cognitive interaction day by day.

sentiment is one's or more than one's out of context (as prior polarity has no contextuality) psychology regarding any topic or concept.


Therefore sentiment is one's or more than one's out of context (as prior polarity has no contextuality) psychology regarding any topic or concept.

involving people is the best way to capture the sentiment of the human society.


We firstly identified two ways to define these distributions: • A linguist gives a verb v per movie, named the referent verb for this movie.

for this movie the initial distribution ∆ 0 = δ v where δ v is the certitude to be on v; 2 Dicosyn is a compilation of synonym relations extracted from seven other dictionaries (Bailly, Benac, Du Chazaud, Guizot, Lafaye, Larousse et Robert).


The main point is that RVCs are semantically compositional and productive, and it has been shown that even very young children can produce novel resultative constructions (Erbaugh, 1992).

not all V 1−V 2 compounds can be found in dictionaries which makes them difficult to align with French data.


Moreover many verb forms were child's talk that were not necessarily present in the resource neither.

we had a serious discrepancy between the experimental data and the lexicographic data.


However, we want to perform a graph analysis of the experimental data as well.

we decided to build experimental graphs that correspond to a restriction of lexicographic graphs to the forms found in the experimental data.


• the appropriateness with the action-video clips: given a meaningful dimension and an actionvideo clip A, is the verbal form v appropriate to the action?

two closed questions per dimension, respectively for the dependency and the appropriateness, enable the qualification of verbs (e.g.


All the current approaches to co-predication are working with a notion of a single argument whose sort is either coerced into another sort or which is itself a product of two different sorts, which are "somehow fused into a single conceptual unit" (Cruse, 2000b, p. 116).

the current approaches implicitly work with a notion that complex arguments represent special sorts containing two component sorts.


Here we want to argue for dependent sorts, which express the notion of "x of type A such that there is y of type B for which relation f (x, y) holds".

dependent sort is not a set theoretic object.


We can make sense of complex phenomena by reification and attribution of properties similar to those of more familiar objects.

of the above assumptions, we argue for "lexical semantics without lexicon" (Elman, 2009).


Tuna cannot be used as an animal and food at the same time frame 6 .

for co-predication to be possible, the two sorts must be able to co-exist.


However, the percentage of correct act-out response is 87%, in which 6% (of the total) does not come with correct oral output.

it seems that for seven-year-olds, correct act-out is strongly associated with correct production, but correct production is not strongly associated with correct act-out.


In their study, the only stimuli were the stories narrated orally by the experimenter, whereas in our study, children were also provided with puppets, instruments, and patient objects to act out the described actions.

either the discrepancy between production and act-out (comprehension) task or additional non-linguistic cues in act-out task may lead to different results of children"s responses.


In the DBS hearer mode, lexical proplets representing function words such as the and a(n) are absorbed into the associated content word proplets.

2 they do not appear in the DBS graphs and must be precipitated during language production in the DBS speaker mode.


This is impossible in K/J and other verb-frame languages; we need a separate clause for the state event after the moving process.

k/J speakers often misinterpret the durative for an hour in (5b) as modifying the process of running.


The object the icicle is quantized but the event lengthen the icicle is not telic.

he proposes that the aspectual behavior of these verbs can be explained in terms of underlying scalar properties of the source verbs, particularly, the structure of "degree of change," d. He posits a degree "increase" function for both positive (such as long) and negative (such as short), having open-Now let us see how telicity is defined.


But we perceive that the incremental objects in (17b,c,d) undergo certain change in their parts and can say they are 'affected' (Lakoff 1970) as well as quantized.

we can possibly represent [load the truck with hay] (pile/spray ---) as a change-of-state lcp with FORMAL = (globally) affected (e2, <2>), AGENTIVE = (e1, move_act (e1, <1>, <3>, <2>).


This equated attribute allows for comparison and pragmatic manipulation by means of logical reasoning uniquely incorporated into the human communication chain.

assuming B is not true, then A is also not true (Modus Tollens or Modus Tollendo Tollens: the mood that by denying denies).


In this case, the wealth of A is not being compared with the wealth of the Queen of Sheba (which would be conceivable), but with the speaker's identity as the Queen of Sheba!

a is like B If a, then B Not B not a The force of denial in these sentences is ultimately based on similarly infelicitous noncompatibility between the implied attributes for comparison:  Let us further observe some unusual syntactic properties of the above sentences, which justify their being classified as "pseudo-comparative sentences".


John is more rich than Mary is beautiful There is in (8a), (8b) and (9) an implied notional comparison of the extent or magnitude of two distinctly different but related attributes: wealth vs beauty, which is possible in English sometimes, but not in other languages, such as Chinese, where only the magnitude of the same attribute may be compared.

(8c), (9a) and 9b -with-Mary-same-has money "Johnson is as rich as Mary" Furthermore, in English the following sentences would be pragmatically problematical: 10.


On the other hand, name transliteration tends to be more conventional than innovative, such that the same chunk is often transliterated in the same way even when embedded in different names.

with our proposed method, the Onset First Principle in phonology was used to syllabify English names and align them with the Chinese renditions.


The reason for the phenomenon in figure 2 is that when the LM weight increases, the language model turns to play a more important role in the whole SMT system.

the decoder prefers to select the translations with higher LM scores, which are also with shorter length and smaller cross-entropy.


By replacing of the λ-operator in the right box with u in the left box, the variable introduced in the left sub-box, namely u, appears in the right sub-box, so the ban on vacuous quantification is satisfied.

the resulting DRS (26b) represents "all police officers caught a criminal (together)."


Scores on the two ends of the scale are relatively rare.

our results show that measuring concreteness from dictionary definitions based on the different defining styles apparently works better for concrete senses than abstract ones.


Unlike Lexical Mapping Theory ((Levin 1986) and (Bresnan and Zaenen 1990)), which handles mapping by assigning intrinsic values to individual roles and grammatical functions, the conceptual semantics approach handles mapping by looking at the conceptual structure of the sentence as a whole.

each interpretation of the sentence would possess its corresponding conceptual structure.


However, as the discussion above, the judgment on the satisfaction might be imprecise.

the adaptive learning, as the most important component of personal search engines, is possibly using the unreasonable feedbacks to mislead the retrieval process.


It can be believed that both factual and satisfactory information normally are relevant search results.

it is unreasonable to affirm that a search result is consequentially either factual or satisfactory.


Obviously the search results in the intersection are the optimal because the satisfactoriness can persuade users to accept the knowledge in the results and meanwhile the factualness can ensure the knowledge is right.

the difference should occur in the two parts outside the intersection: Relevant search result Factual information  Factual but not satisfactory (abbr., FNS) search results.


And especially, the differences between the SBC and SAC are very small.

if it is right that users cannot determine the factualness by only checking the title or/and snapshot of feedback (actually the low precision has proved this), the small difference between the SBC and SAC may illustrate users normally are not aware of what is the factual information.


Here, it is necessary to note that the reducing trend of each curve in the figures should be neglected because the practical number of clicks at the higher patience level is really small.

the factual perspectives should be the height of the whole curve in the two-dimensional space and the height difference among the curves.


The characteristics illustrate that the mood swings of users normally occur after going deep into the details of feedbacks but not in the process of browsing the result list.

why will the details make users have the obvious mood swings?


According to the quantitative evidences, we can conclude the main advantages of highly ranking factual feedbacks: 1) Help users cognize factual knowledge quickly; 2) Avoid to puzzle users in the process of surveying factual knowledge; 3) Reduce the probability of negative mood swings occurring.

compare to the satisfactory feedback, the factual one can not only supplies trustworthy information service but also improve the user experiments.


The underlying principle is that the more the number of the similar sentence pairs with high quality is, the better of the quality of the sentence pair is.

cSP represents the quality of the sentence pair.


If f σ or c σ is too large, it will decrease the edges in the graph, and make the isolated sentence pair increasing; on the other hand, if f σ or c σ is too small, there will be too many edges, weakening the ability of distinguishing the importance of sentence pair using the structural information.

we should try to find a balance between avoiding too many isolated sentence pairs and avoiding too many connected sentence pairs.


Taking the above two steps, it avoids updating and sorting the importance of each sentence pair that the selected sentence pair can reach through a connected path.

the pseudo code of the final algorithm is shown as follows: Selected Sentence List S 1: S = <> ; 2.